The Rise of the Chief Experience Officer

This transcript was created using AI tools and is not a verbatim transcript of the episode. Please forgive any spelling and grammar errors that may be included. 

Courtney: Customer acquisition costs are rising. Marketing budgets are flat. Does that have to mean fewer customers?

Not if the Chief Experience Officer and AI have anything to say about it.

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era. As always, I’m joined by Knownwell CEO David DeWolf, Chief Product Officer Mohan Rao, and Chief Strategy Officer Pete Buer. We also have a discussion with Daniel Salvato about using AI to drive customer growth. But first, fill up those canteens and put on your sunscreen because it’s time for another AI in the Wild.

Courtney: The biggest news in AI this week wasn’t specifically about artificial intelligence, it was about Apple Intelligence. Pete, what can you tell us about this week’s big news coming from Cupertino?

Pete: Well, I know our segment’s called, uh, AI [00:01:00] in the Wild, but it looks like Apple intelligence picking season will be in the fall. But it. that, here’s what we can expect. The, uh, main thrust is a revamp of Siri. Transforming the voice assistant into a personal agent, able to handle more complex requests.

Use your personal context in shaping responses to your questions, and even offering proactive suggestions the question you didn’t think to ask. Secondarily, it’s gonna be working in the background of Apple devices, trying to help optimize the user experience, optimizing performance, extending battery life, uh, and personalizing services across the apple.

Device line also cranking up the quality and presence of Apple’s, augmented reality. Pretty cool stuff. But, um, stock price and reporting on Monday was kind of a bit of a meh, flat across the day and commentary.

Almost having a disappointing feel to [00:02:00] it. There were no real surprises in the announcement. Apple had leaked a fair amount of what was coming. and the functionality as I just described, it a little bit of a conservative feel to it, doesn’t it? Kind of the basics, if you’ve been keeping up with what’s going on in generative AI elsewhere.

In the world. And I don’t know, maybe that’s not enough to sell phones, but personally I love the conservatism for this moment in time. too many people count on their Apple devices to run their lives sometimes with their livelihoods at stake. Um, and the acumen level of users, stretches all across a, a spectrum.

AI is absolutely new to some and old hat for others. I’m thinking there’s nothing but downside to releasing some kind of a half-baked for the point of splash here. And Courtney will, uh, remember the h and r block and QuickBooks, uh, uh, uh, assistance who

Courtney: Yes.

Pete: back in the day advising, uh, on, [00:03:00] on, on tax treatment and putting people in jail.

And so, other cool thought on this one. Um, Apple is kind of doing the work for every other corporation out there in the world right now, helping with the change management effort to get. Employees of all types, comfortable using ai, familiar with the technology so that when in the corporate setting, generative AI gets deployed, it gets deployed more successfully.

And so that’s, I think another, like, there’s just so much hanging in the balance. since Monday, Apple’s been trading up, it’s over 10% last time I looked. So maybe a couple of these second, third order considerations are kicking in. A closing thought on this one. Courtney and I saved the best for last.

Um, Siri will now also work across all of the other apps on the phone, integrating information and pulling from them as needed from whatever the, you know, user request might be [00:04:00] beyond being incredibly useful. I think that answers a question that we’ve been kicking around here for a long time, about whether consumers need a second handheld device.

crawl through the first one. We knew it was coming, but how ironic that this news would hit on the exact day. My Rabbit r1 hit the mailbox.

Courtney: That’s amazing.

Pete: Little bunny fooo. We hardly knew you.

Courtney: Yes.

Well, here’s my thought on both of these. Finally. Finally on Apple side and finally on the rabbit side. I feel like both of these things are things that I feel like should have happened several months ago, so, but I am excited to use them personally, especially the upgrade to Siri on my own device. Pete, thank you as always.

Pete: Thank you.

​

Courtney: What role will AI play in driving [00:05:00] client growth and customer acquisition in the years to come and is the Chief experience officer, the chief marketing officer of the past decade? I sat down recently with David Dul and Mohan Rao to talk about those topics and more.

David Mohan. I don’t know if you ever have these moments, especially in your functional area. If you ever think back to, you know, a previous time, previous decade and think, man, that was the sweet spot. That was the good old days. We didn’t even realize it. For the CMOs out there, you, maybe you will, I might be speaking your love language right now, but in the 2010s it was.

It was the time for the CMO acquiring customers was really affordable. We were in the age of digital marketing.

David: Mm-Hmm

Courtney: It was working so well.

David: mm-Hmm.

Courtney: Now, [00:06:00] unfortunately, we’ve kind of come to the other side of that. Acquiring customers is, you know, more expensive than ever yet. Marketing budgets are the same. So much of what worked back then no longer works.

And I have a premise that we are on that same path with client growth.

David: Hmm.

Courtney: So if that was true for the CMO. Just a few years ago, the glory days. I sound really old now.

David: You’re

Courtney: The glory days remarket. Yes.

David: it.

Courtney: Yes. Um, I think, I suspect that we may be in a, that same season for client growth, and I’m curious to get your two points or your two perspectives on how AI is playing into client growth.

David: that’s fascinating because, um, if you think about it, why, why did digital marketing take off? What was it that really put the CMO back on the [00:07:00] map? And I, I would say, and I’ve written before about how the CMO, during the, the digital. Revolution really came into their own and became a full fledged member of the c-suite again.

Um, I think it’s because media of the time was measurable in a way that previous forms of media were not measurable. Right. Um. We had the ability to measure click-through rates and the cost of acquisition and those types of things in a very new way that allowed marketers to run a very disciplined operating machine to drive results well.

I think that was well and good, and I think all functions of business should go through that when they can. But it has been really hard for aspects of the business that aren’t measurable inherently, and that [00:08:00] can’t do math to figure out. Their metrics, and I think that what you’re talking to is this reality in customer success, right?

Customer success, client management, account management, these types of things, especially in B2B, professional service organizations have inherently been relational, not transactional.

Courtney: Yeah.

David: relational and not transactional, you can’t measure it. think what AI does is give us the ability to actually transform this communication, this natural exhaust of the business, of the, the relationships that we call communication and transform it into true operating metrics into.

we can use to drive performance execution. And I think when that happens, we are gonna see a revival of the effectiveness and the [00:09:00] efficiency with which we serve and manage our commercial relationships.

Mohan: Yeah. You know, I think I get to the same answer in a slightly different way. Uh, Courtney, first of all, it’s a brilliant question. Uh, so as I was thinking of David’s answer, which makes a lot of sense, uh, the, if I think the question is, can customer success be a growth driver, right, in this new era? And the answer is clearly yes.

And the reason why it is possible now through AI is because of two fundamental things. Um, David just touched on one, which is historically it was a reactive function. Now there is truly a chance to be proactive and be able to anticipate clients’ needs. proactive in how you engage with the client.

David: Mm-Hmm

Mohan: is a fundamental difference from where we were to what’s possible today. second is we are able to [00:10:00] personalize client experiences at scale. That was not

Courtney: Hmm.

Mohan: It used to be all clients with the same, and we really strived for uniformity, right? Even if the, it was dumbing down the mean,

David: Mm-Hmm

Mohan: we were uniform.

That’s what we used to aim for. And now it’s possible to personalize at scale. That was not possible before. So I’d say those are the two reasons why, uh, customer success can truly be a growth driver in today’s age.

David: I think Mohan, um, maybe even more brilliant than Courtney’s Framing is your answer. I think those two, uh, uh, points are right on, right, the ability to be proactive and the ability to personalize in new ways. I mean, that’s ultimately when you think about exceptional client service, that’s what it’s about.

Like in fact, as we have been going through our research and looking at. What are the true drivers of commercial health and [00:11:00] creating these long-term growing commercial relationships? We have found that in the data that over and over again, the drivers are things like being proactive, being incredibly responsive, right?

Or two big drivers. The personalization, like having a relationship and the health of that relationship and how you’re able to really personalize that experience really matters in services. Um, so I think those are spot on. I also think about, um. The other part of the equation, the one I was thinking about as you were starting off was we have found in the research that, um, one of the big categories that drives commercial health is the delivery quality perception.

And what’s really fascinating here is that most firms measure delivery quality. And so you’d think, man, we should be nailing this. But what they don’t measure is the perception, which again, is that personalized aspect of it is how is that received by the [00:12:00] buyer? How is that perceived by the client?

Because it’s the perception that matters. It’s not whether you follow your quality control process or you know, this. X, Y or Z processor standard, right? What matters is, is it received that way, and that again speaks to that personalization. And so I think we have this new ability that’s right on our fingertips that I.

client service professionals should all be craving more of. And, and as we get there, what I get really excited about is I actually thinking serving clients is not a customer success job. Alright? That works in SaaS. It works in in software business. It does not work in a professional service business.

It’s a full company job, and so what we can start to do is actually scale what’s been impossible to scale because the firms that do this, well do it with a partner model where it’s individuals that are [00:13:00] delivering that. What we can start to do is institutionalize what we have not been able to institutionalize before to allow that proactivity and that personalization.

Courtney: So David Mohan, earlier in the fall, we made a statement about the CHRO and that maybe. this moment was their moment to rise up in the organization and really have a new era, uh, for that role. A different looking kind of, if you think about it, what you said about A CMO. I know you said just a second ago when it comes to services, you know, it’s really the whole organization, but I do think sometimes there are certain people in an organization that really start to make that change.

What role do you see has. The possibility to kind of have a new seat at the table, especially when it comes to the executive team.

David: I think you’re just trying to point out the fact that while I might’ve gotten the prediction on Amazon, [00:14:00] right, that I got this one wrong on the CHRO. Is that what you’re, you’re pointing No, I,

Courtney: No, but now that you pointed out, uh, yes.

David: here. Here’s the thing Whether it is A-C-H-R-O who’s in charged with the employee experience, it is the chief client or chief customer officer, which is charged with the client slash customer experience. I think it’s all about that experience. What did Mohan speak to? The personalization, the, the proactive.

I think those are the types of things that drive experience and so maybe it’s the chief experience Officer. I do think though, what’s most important is actually it’s, it’s not the role, it’s not the title. It’s actually that capability of creating more human connection, allowing us being the tool that allows.

Us to do what we as humans can do better than anybody else, which, and only we can [00:15:00] do, which is build relationships with each other, right? And that experience of relationship and really supporting the process of business rediscovering humanity, I think is actually what it’s all about.

Mohan: You know, we’ve also, uh, discussed AI as the scaling source. So when you think about phrases like personalization, um, at scale, it is a confusing term, right? How can you personalize and be at scale, right? So, uh, but that’s, that’s the segment of one, uh, that, uh, was not possible before because you grouped customers together and you try to give them uniform service.

But now what you can do is you can treat these customers as a segment of one and do the right things by them and proactively at that. Uh, that’s where I think the secret here is to make, um, your existing clients a growth driver. I.

Courtney: David Mohan, thank you as always.

Mohan: Thanks, Courtney. Thanks David.

David: [00:16:00] brilliant.

Courtney: I like it. We’ve talked a lot on this show about the client retention imperative for professional service companies. Now we have a playbook you can follow to start incorporating AI into your client retention efforts. Go to Knownwell dot com slash playbook today.

There you can download the latest brainchild from our Chief Strategy Officer, Pete Er, and learn how to ensure your most valuable resource, your clients remain. Just that

Courtney: Pete Buer sat down with Daniel Salvato of New Spring Capital recently to hear how their portfolio companies are using AI to drive growth and scale.

Pete: Daniel, welcome. It’s so great to have you on the podcast.

Daniel: Thank you, Pete. Great to meet you as well, and glad to be on.

Pete: Let’s give our listeners a little context for the, the conversation. If we can. Can you, um, give us the, the high points on NewSpring [00:17:00] and your role?

Daniel: Sure. Give you a little background here. So NewSpring Capital is around a three and a half billion dollar asset manager. It’s got nearly a 25 year track record of providing lower middle market. Often founder owned, family owned businesses with capital solutions, ranging from mes, debt to growth equity to majority recaps.

And within the NewSpring Capital umbrella, I’m a principle with New Spring Holdings, which is our dedicated buy and build strategy in the tech enabled services space. So what we do is build platform companies and thesis areas. We believe we’re aligned with prevailing macro trends through a combination of targeted m and a and methodic organic growth.

Once we acquire a platform in one of these areas, we surround the company with seasoned industry leaders. We want to help the founder on this journey, and we begin quickly investing in organic growth initiatives and key infrastructure to support scalable operations. And then on the m and a side, our model typically entails supporting our platforms, execute five to 10 deals, which are all highly strategic and become [00:18:00] fully integrated into the final product.

Pete: Awesome. Thank you. And as you know, this is an episode that’s about, using AI to help drive customer growth. I heard growth several times in your setup, so let’s, let’s start there. what’s your take on how portfolio companies are looking at AI as a mechanism for brand growth?

Daniel: Yeah, look, it’s a, it’s a great question and it, this is a frequent topic of discussion with all of our management teams. of the companies in our portfolio are really service providers, and what we’ve seen is a lot of encouraging signs from those who have leaned into the technology to fuel productivity gains in everything from customer acquisition to delivery execution.

To administrative support functions. And to give you a few just real world examples out of our portfolio, we’ve got a business called Underdog and Company that’s in the sports, entertainment and culture marketing space. They’ve been using it to actually create content, both kind of marketing, uh, outbound communications [00:19:00] things for their clients.

It’s really accelerating the way that they’re able to create content and get that out into the world. Core, they’re a government contracting company that primarily serves the intelligence community. They utilize AL and ML routinely as part of their core execution of data visualization and also analysis as a service.

And another example would be Wealthcare. They’re an RIA, and they’ve been using it to accelerate a lot of their outbound BD communications. so apart from some of these kind of discreet port code use cases, I would say we at New Sprint Capital are also using the technology pretty heavily. So believe that competency in, in harnessing AI will be a real differentiator among private equity firms.

And so we’ve been developing use cases internally that include everything from research, information synthesis, data engineering, and content creation, and then trying to share these learnings and practices. Down to our portfolio companies [00:20:00] and creating tools and applications that they can actually use and incorporate into their own execution.

Pete: Awesome. Tons of activity at the company level with leadership teams pushing on their own and then. Support from you, uh, as an investment banker. What do, what does that second process look like? Are you, do you sort of make yourself available to them? Do you have them do, um, strategy reviews and figure out how you can engage them?

Do you have a task force that circulates among, uh, portfolio companies to try to help them figure out how to adopt ai?

Daniel: Yeah, so I think what’s a little bit unique about our model is our portfolio is really meant to just be a handful of companies that we’re building kind of significant size. Platforms out of. And

Pete: Yep.

Daniel: we stay deliberately concentrated like that

Pete: Yep.

Daniel: that we can be very enmeshed in what they’re doing day to day.

And I think that additional connectivity just allows us to have that kind [00:21:00] of open dialogue and understand are they sort of experiencing as a barrier to growth, and are there ways that we can help them find solutions either internally or externally develop. That can help break down some of those barriers to do things more efficiently and be able to grow faster.

And so in some cases that that involves going kind of outside, outside of us, uh, to get resources that can help them scale. And in other cases it’s things that we develop in house and can allow them to leverage, um, on their own journey.

Pete: Nice. So it’s kind of like you’re a member of the team and you’ve got intimacy, proximity, and you’re just part of the conversation

which strike.

Daniel: way to describe it.

Pete: That strikes me as the, the best way to go. How, how do you know when a company’s really got lock on a great idea?

Daniel: So I think it’s important, um, that every company is kind of having a pipeline of ideas that they’re always [00:22:00] working through. I think you never want the company to go kind of into a black box and try to emerge months later with a perfectly refined new idea to test. So I think you want that kind of.

Sandbox where companies feel empowered to be constantly iterating and testing new ideas on a smaller scale to see if they’re getting traction, if they’ve got that lock, and if you have that kind of creativity that’s embedded in in the operations, then every now and then something’s gonna stick and you’re gonna notice that it’s working.

Either it’s getting great feedback from customers or you’re seeing new clients, one because of it. there’s a lot of kind of early signals that can point to the success of an initiative like that, and I think that’s when we find it’s the right time to pour more fuel on the fire, give them the capital and the empowerment to, uh, expand on what’s working.

I.

Pete: Nice. So you’ve, you’ve described your, your process for helping to enable growth, and you’ve shared some great [00:23:00] examples of how companies are driving growth. How about the competitive landscape? How is AI gonna change, um, what your portfolio companies are up against?

Daniel: Yeah, so look, I, I think the old machine learning paradigm, what you used to see was that large companies would. Have huge data sets that they would use to train their own proprietary models to try to eke out an incremental advantage. And, you know, that would allow them to kind of fare much better than smaller companies who had less data and no resources in terms of data science to actually do what the larger companies were doing.

And so it was very much a, a world of the haves force, the have nots when it came to kind of modeling and, and data science. what’s happened now is that large scale AI models and LLMs are really leveling the playing field. and that’s because the hugely expensive endeavor of training these all purpose models is really being absorbed by just a handful of [00:24:00] large tech companies, and they’re making it widely available.

GPT-4 is reported to have cost around a hundred million dollars to train and has over a trillion different inputs, but you can use it for 20 to $30 a month. and I think what that means is, you know, setting aside maybe some incremental advantages that large companies have from fine tuning models and building infrastructure on top of them, mid-market company can use chat GPT and open AI’s models just as effectively as a large company to do research, generate content, and sort of break down some of those barriers and scale requirements that may have made it harder to execute on new ideas previously.

And so what I think this is gonna really drive is, is a new paradigm where the differentiator can come from, who can be most nimble and creative in thinking of new ways to innovate in their markets. And that’s where we think that mid-market companies have really always excelled.

Pete: Nice. So [00:25:00] as a small company, you’ve got a once in a generation chance to play on a level field and go up against the big guys with a, with a pretty darn good shot at succeeding.

Daniel: Yeah, I, I think that’s right. And you know, I think just as a, you know, point of reference, things are increasingly moving further and further down market. Um, my colleague Lee was actually on this podcast

Pete: Okay. Yep.

Daniel: And he was talking about copilot and how that was initially only gonna be available to Microsoft’s largest corporate customers at that time.

Well, now that’s, you know, available to everyone. We’ve got access to copilot and we’ve been using it for our own internal operations. And I think what you find is that of these bandwidth constrained teams in the lower end of the market. These tools are a real kind of multiplier and they allow these companies to do a lot more with their existing employees than they could have ever done previously.

And I think that actually stands in contrast with some of what we’ve seen at the larger end [00:26:00] of the market where you’ve seen a lot of announcements of things like layoffs where, you know, IBM said they’re gonna replace thousands of roles with kind of AI solutions and they’re making cuts in marketing and communications.

And so I think. While the smaller companies are doing more with the people they have, some of the larger companies are trying to do the same thing with less people. And that’s where I think this technology really starts to favor these emerging middle market companies with, with new ideas that they want to scale.

Pete: You’ve got a relatively unique perspective here too, in that you were. uh, an operator, CEO, uh, prior to your time as an investor, you must feel empathy for the people in the top seat. What’s, what’s the hardest for them right now?

Daniel: look, I think one of the challenges with. Machine learning data science and AI is always how to make it useful because it on the [00:27:00] surface sounds very interesting, sounds very novel. You’re getting pressure from your investors, from your directors to make sure that you’re at the forefront of utilizing this.

And then it’s gonna be on your shoulders to ensure that the, that execution goes very well and actually delivers value to those shareholders and to your company. I think in the case of, of above, um, the, the lending industry had been using data science and AI for a long time in the form of machine learning ensemble models, and.

that to do everything from targeting customers, underwriting loans, monitoring their portfolio. Um, and that was a long time before LLMs really brought AI more into the public consciousness. But two of the things that I think I learned in going through that experience that I think are kind of valuable for many executives who, who may be in, in that same position now.

to first, uh, don’t underestimate the need for real [00:28:00] perseverance in tackling some of the foundational issues here. So before your models are gonna be producing interesting, useful, um, outputs, you’ve gotta do that. Blocking tackling of the data engineering, the data hygiene, getting everything organized and structured so that you can get useful outputs from the models that you end up building.

And. Uh, that’s always hard work. Uh, but the longer you wait to do it, it, it just gets harder because the more and more data gets incorporated there. And then kind of of guidance that I would offer is these machine learning models. And that’s whether we’re talking about kind of old school random forests new LLMs.

very good at using a massive amount of data to answer a specific question. Uh, but the art really becomes. How do you figure out what are the right questions to ask, and then what judgements do you apply to those answers? So if I was an [00:29:00] executive, I’d say now that the, the computational exercise of kind of mathematically answering these questions becoming a lot easier with AI tools, what they should be focused on is how can their organization be pointing them in the right direction to ask those questions and do useful things with the answers that come out of it.

Pete: Daniel, thank you so much. It’s been a a pleasure. Great to meet you and really appreciate all the thinking and insight.

Daniel: Thank you Pete. Really appreciate it.

Courtney: thanks as always for listening and watching. At this point in the show, I usually ask you for a rating or a review, but today I’m gonna ask you for something different. Would you go into your podcast player right now and just hit the follow link? This is another great way to help more people discover the show.

At the end of every show, we like to ask one of our AI friends for them to weigh in on the topic at hand. So, hey Perplexity. Welcome back to the show again. This episode we’re talking about the role of [00:30:00] the chief experience officer in the age of ai.

what do you think their role will be?

Ian: The chief experience officer’s role will evolve to oversee the seamless integration of AI into customer experiences, ensuring AI enhances rather than hinders interactions. They’ll collaborate closely with data and tech teams to implement AI responsibly, ethically, and in a human-centric way.​

Courtney: And now you’re in the know. Thanks as always for listening or watching. We’ll see you next week with more headlines, round table discussions and interviews with AI experts.